Emergence of Equilibria from Individual Strategies in Online Content Diffusion

Social scientists have observed that human behavior in society can often be modeled as corresponding to a threshold type policy. A new behavior would propagate by a procedure in which an individual adopts the new behavior if the fraction of his neighbors or friends having adopted the new behavior exceeds some threshold. In this paper we study the question of whether the emergence of threshold policies may be modeled as a result of some rational process which would describe the behavior of non-cooperative rational members of some social network. We focus on situations in which individuals take the decision whether to access or not some content, based on the number of views that the content has. Our analysis aims at understanding not only the behavior of individuals, but also the way in which information about the quality of a given content can be deduced from view counts when only part of the viewers that access the content are informed about its quality. In this paper we present a game formulation for the behavior of individuals using a meanfield model: the number of individuals is approximated by a continuum of atomless players and for which the Wardrop equilibrium is the solution concept. We derive conditions on the problem's parameters that result indeed in the emergence of threshold equilibria policies. But we also identify some parameters in which other structures are obtained for the equilibrium behavior of individuals

WING/WORLD: An Open Experimental Toolkit for the Design and Deployment of IEEE 802.11-Based Wireless Mesh Networks Testbeds

Wireless Mesh Networks represent an interesting instance of light-infrastructure wireless networks. Due to their flexibility and resiliency to network failures, wireless mesh networks are particularly suitable for incremental and rapid deployments of wireless access networks in both metropolitan and rural areas. This paper illustrates the design and development of an open toolkit aimed at supporting the design of different solutions for wireless mesh networking by enabling real evaluation, validation, and demonstration. The resulting testbed is based on off-the-shelf hardware components and open-source software and is focused on IEEE 802.11 commodity devices. The software toolkit is based on an "open" philosophy and aims at providing the scientific community with a tool for effective and reproducible performance analysis of WMNs. The paper describes the architecture of the toolkit, and its core functionalities, as well as its potential evolutions

Connectivity in Ad-Hoc Networks: an Infinite-Server Queue Approach

In this paper we present some extensions on previously published results regarding connectivity issues in one--dimensional ad--hoc networks. We show how an equivalentGI|D|\infty$ queueing model may be used to address the issue, and present connectivity results on both infinite and finite networks for various node placement statistics. We then show how a GI|G| model may be used to study broadcast percolation problems in ad--hoc networks with general node placement and random communication range. In particular, we obtain explicit results for the case of nodes distributed according to a Poisson distribution operating in a fading environment. In case of nodes distributed according to a Poisson point process, heavy traffic theory is applied to derive the critical communication range for connectivity and the critical transmission power for broadcast percolation in dense networks. The analysis is then extended to the case of unreliable ad--hoc networks, with an in--depth discussion of asymptotic results

Coverage and Connectivity of Ad-Hoc Networks in Presence of Channel Randomness

In this paper we present an analytical procedure for the computation of the node isolation probability in an ad-hoc network in presence of channel randomness, with applications to shadowing and fading phenomena. Such a probability coincides with the complement of the coverage probability, given that nodes are distributed according to a Poisson point process. These results are used to obtain an estimate of the connectivity features for very dense networks. For the case of superimposed lognormal shadowing and Rayleigh fading, the connectivity improvements achievable by means of diversity schemes are investigated

Towards automated privacy compliance checking of applications in Cloud and Fog environments

International audienceInternet application users are increasingly concerned about the way applications handle their personal data. However, manually checking whether applications actually respect the claims made in their privacy policy is both error-prone and time-consuming. This paper claims that the privacy compliance of applications hosted in cloud or fog computing platforms can and should be automatically carried by the platform itself. We discuss the feasibility of unintrusive and application-agnostic monitoring in the platform layer to check the privacy compliance of applications. First, the platform may monitor an application's privacy-oriented behavior through signals such as its network traffic characteristics. Second, these signals can be analyzed and compared with the principles found in the application's privacy policy. We present a procedure based on machinelearning techniques to identify the type of data being shared by applications with external third-parties even if the application uses encrypted communications. Our classifiers identify traffic samples of applications with 86% accuracy

Good Shepherds Care For Their Cattle: Seamless Pod Migration in Geo-Distributed Kubernetes

International audienceContainer technology has become a very popular choice for easing and managing the deployment of cloud applications and services. Container orchestration systems such as Kubernetes can automate to a large extent the deployment, scaling, and operations for containers across clusters of nodes, reducing human errors and saving cost and time. Designed with "traditional" cloud environments in mind (i.e., large datacenters with close-by machines connected by high-speed networks), systems like Kubernetes present some limitations in geo-distributed environments where computational workloads are moved to the edges of the network, close to where data is being generated/consumed. In geo-distributed environments, moving around containers, either to follow moving data sources/sinks or due to unpredictable changes in the network substrate, is a rather common operation. We present MyceDrive, a stateful resource migration solution natively integrated with the Kubernetes orchestrator. We show that geo-distributed Kubernetes pod migration is feasible while remaining fully transparent to the migrated application as well as its clients, while reducing downtimes up to 7x compared to state-of-the-art solutions

Evolutionary Epidemic Routing

We introduce a framework which allows forwarding schemes to evolve in order to adapt to changing and a priori unknown environments. The framework is inspired by genetic algorithms: at each node a genotype describes the forwarding scheme used, a selection process fosters the diffusion of the fittest genotypes in the system and new genotypes are created by combining existing ones or applying random changes. This framework is illustrated through a simple case study and simulations are undertaken to evaluate its performance